Tutorials

Deeplearning4j Tutorials

While Deeplearning4j is written in Java, the Java Virtual Machine (JVM) lets you import and share code in other JVM languages. These tutorials are written in Scala, the de facto standard for data science in the Java environment. There’s nothing stopping you from using any other interpreter such as Java, Kotlin, or Clojure.

If you’re coming from non-JVM languages like Python or R, you may want to read about how the JVM works before using these tutorials. Knowing the basic terms such as classpath, virtual machine, “strongly-typed” languages, and functional programming will help you debug, as well as expand on the knowledge you gain here. If you don’t know Scala and want to learn it, Coursera has a great course named Functional Programming Principles in Scala.

The tutorials are currently being reworked. You will likely find stumbling points. If you need any support while working through them, feel free to ask questions on https://community.konduit.ai/.

Tutorials covering basic DL4J features

pageQuickstart with MNIST

pageMultiLayerNetwork And ComputationGraph

pageLogistic Regression

pageBuilt-in Data Iterators

pageFeed Forward Networks

pageBasic Autoencoder

pageAdvanced Autoencoder

pageConvolutional Networks

pageRecurrent Networks

pageEarly Stopping

pageLayers and Preprocessors

pageHyperparameter Optimization

pageUsing Multiple GPUs

End to End Tutorials showing specific solutions

pageClinical Time Series LSTM

pageSea Temperature Convolutional LSTM

pageSea Temperature Convolutional LSTM 2

pageInstacart Multitask Example

pageInstacart Single Task Example

pageCloud Detection Example